The manner in which humans interact with computing devices is rapidly evolving and has reached the point where human users can access services and resources on the Internet using natural language. Speech recognition software tools continue to improve in terms of the fidelity with which human speech is captured despite the tremendous variation with which the input is delivered. However, there is still considerable work to be done with regard to making such input understandable to machines. That is, in order for a user's verbal request to be fulfilled, not only must the input be accurately and reliably captured, but the semantic meaning the input represents must be accurately and reliably translated to a form with which a machine can work. The extent to which the accuracy and reliability with which the input is entered or captured is compromised, this goal is undermined. For example, if the user is entering the input in a text interface, misspellings (either by the user or an auto-correction feature of the interface) and grammatical errors can result in the received text being radically different than the intended semantic meaning. In the context of speech recognition, misrecognition of words and phrases can lead to similar results.